Do Young, Female, and Experienced Characteristics of Risk
Oversight Committee Members Accommodate Bank Risk-Taking?
Evidence from Indonesia
Aulia Natasya Irfani Ampri and Ancella Anitawati Hermawan
Department of Accounting, Universitas Indonesia, Depok, Indonesia
Keywords: Risk Oversight Committee; Risk-Taking; Young; Female; Experienced
Abstract: Although risk oversight committee has been mandatory for Indonesian banking industry since 2006, there has
never been any inquiry trying to understand how the characteristics of risk oversight committee members may
impact their tolerance towards bank management risk-taking. Specifically, this research is aimed to shades
light on how young age, female, and risk management experience characteristics of each members affect their
inclination towards accommodating bank risk-taking. The study uses panel data random effect regression for
unique dataset of 27 banks from 2012-2016 and find that contrary to popular belief, increasing number of
younger members reduce accommodation to bank risk-taking. Moreover, increasing female members
composition is proven to rise bank risk-taking. These results are different with increasing proportion of risk
management experienced committee members as they are proven to have no significant effect towards bank
risk-taking behaviour. Additionally, sensitivity tests conducted using average age as young indicator and
loosening risk management experience criteria by including previous risk oversight committee experience
prove that these characteristics are not impacting bank risk-taking. However, presence of female members in
risk oversight committee have significant impact on improving accommodation to bank risk-taking.
1 INTRODUCTION
The banking industry is a highly volatile industry
in which failure of a bank could destroy the whole
system simultaneously and unexpectedly (Talavera,
Yin, & Zhang, 2018). Moreover, as the nature of
banking is as intermediary institution between those
who have excess money and in need of money
(Undang-Undang No. 10/1998), banks are obliged to
have high-quality governance. The enormous amount
of public funds on its hand and high possibility on
making global crisis due to the high interconnection
makes the banking industry in need of exceptionally
good bank governance (BCBS, 2015).
Banks are facing risks on daily basis (POJK
18/POJK.03/2016). The amount of risk taking,
furthermore, is an important matter. Bank must
manage the risk and reward opportunity cost of the
industry (Haneef, Rana, & Karim, 2012). In order to
ensure executive risk management and risk-taking
decisions, board of commissioner is obliged to create
risk oversight committee (POJK 18/POJK.03/2016).
Although the committee existence is obliged since
2006 (PBI No. 8/4/PBI/2006), there are still very
limited research investigating risk oversight
committee effectiveness and characteristics. Apart
from the fact that most research limits itself to
exclude financial industries (Battaglia & Gallo, 2015;
M. Mayur & Saravanan, 2017). Andarini&Januarti
(2012) expressed that previous research on board of
commissioners' committees are only observing audit
committee as well as nomination and remuneration
committee. Subramaniam et al. (2009) infer that the
phenomenon is due to the lack of empirical
information regarding the characteristics of risk
oversight committee and the fact that the committee
is still relatively new.
Aiming to answer the said question, this research
explores the relationship between gender, age, and
risk management experienced members of banking
risk oversight committee to their tolerance towards
bank risk-taking. It is interesting to deeply explore
this field as the inherent nature of younger age,
female, and experienced characteristics to risk-taking
previous research each contains conflicting views
(Hirshleifer&Thakor, 1992; Serfling, 2014; Harris et
Natasya Irfani Ampri, A. and Anitawati Hermawan, A.
Do Young, Female, and Experienced Characteristics of Risk Oversight Committee Members Accommodate Bank Risk-Taking? Evidence from Indonesia.
DOI: 10.5220/0008436900650074
In Proceedings of the 4th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2018), pages 65-74
ISBN: 978-989-758-387-2
Copyright
c
 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
65

al, 2007; Adams & Funk, 2012; Eichner and Lachner,
2017; Garcia-Sanchez, Garcia-Meca & Cudrado
Balles; 2017). Through unique hand-collected data of
Indonesia conventional banks from 2012 to 2016, this
paper is also filling the vacuum of knowledge on
emerging country bank risk-taking behavior as most
risk-taking studies in Asia are conducted in China and
India (Battaglia & Gallo, 2015; Liang et al., 2013;
Talavera et al., 2018). As far as it could be
ascertained, this is the first study showing how young
age, gender, and risk management experienced risk
oversight committee member characteristics is
relevant to bank risk-taking in a way consistent to
bank highly regulated environment. This study would
provide insights to regulators for an ideal composition
of bank board; to investors so they could invest in
banks with similar risk appetite; and to Board of
Commissioner to pick the right candidates suiting
bank risk-appetite.
2 LITERATURE REVIEW AND
HYPOTHESES DEVELOPMENT
2.1 Risk-Taking
Risk-taking is the option on taking unsafe
decision by the company among the pool of other
possible decision. Risk-taking choices are made on
the range of risk appetite or the extent an organization
would like to take risk. Risk-lover organization tends
to make many risky decisions while the risk averse
organizations are less inclined to take risk.
There are various internal and external
motivations underlying risk-taking behavior.
Atkinson (1957) found that there are two chains of
activities related to this: (1) acknowledging
individual reasons for choosing an action compared
to other actions and (2) measuring the implications of
the treatment. He then argues that motives,
expectations, and incentives determine the risk-taking
action of an entity. Fan et al. (2016) add that
competition motives, an external factor, does not
increase the risk-taking behavior by banks. Reducing
regulation in banking activities can increase
competition and make the banking industry more
stable.
Risk-taking behavior can have a positive and
negative impact on the company. IFC (2012) explains
that risk-taking can have a positive impact when (1)
the company can perform good operational
management so that cash inflows are higher than
existing assets, (2) firms can manage risk-taking
reinvestment with high profits and support corporate
growth, and (3) company risk-appetite in accordance
with measured risk tolerance. However, excessive
risk-taking behavior can lead companies to make
uninformed decisions and result in large losses to
stakeholders.
Acknowledging that bank main line of
business is as an intermediary between those who
have more money to those who does not, the amount
of lending that banks give to certain type of customers
becomes an area of concern (Dong et al., 2014;
Skała& Weill, 2018). The collapses of banking
industry rise as a result of higher non-performing loan
(NPL) that further contributes to credit risk. Bank
assets are mostly made up of loan while liabilities are
deposit payable so the mismatch between both would
cause greater credit risk (Waemustafa&Sukri, 2015).
In other words, increasing share of non-performing
loan may cause large losses in banks as higher gross
NPL ratio is correlated to higher direct ex-post means
of credit risk (Srairi, 2013). hat different age shows
different tendency of behavior. These differences are
often categorized into two: the older generation and
the younger generation (Berger, Kick, &Schaeck,
2014; Ferrero-Ferrero, Fernández-Izquierdo, &
Muñoz-Torres, 2015; Hertel, I.J.M. Van der Heijden,
H. de Lange, & Deller, 2013; Menkhoff, Schmidt,
&Brozynski, 2006; Talavera et al., 2018). One of the
behavioral impacts of this age differences situations
and become the focus in many researches are how age
impacts someone to make decision.
2.2 Young Age
Aging are associated to neuromodulator changes
for integration of information (Mata, Josef, Samanez-
Larkin, &Hertwig, 2011; Mata, Schooler,
&Rieskamp, 2011; Mata, von Helversen,
&Rieskamp, 2010). Decline on cognitive ability such
as memory may lead to older adult makes simpler
decision and more error if information is combined.
Moreover, motivational theories explain that aging
leads to greater focus on emotional goals which leads
to informational processing bias (Mather
&Carstensen, 2005). These differences in
anticipation are a potential system leading to
differences on risk-taking decisions (Mata et al.,
2011).
The younger generations are stereotyped of
having different characteristics compared to the older
generation. The older generation is found to be
stricter, risk-averse, and less creative. This is due to
the accumulative understanding that they obtain from
longer life (Talavera et al., 2018). The younger
generation, however, are often labelled to have 180
degrees differences from the older generation. They
are viewed to be more adventurous, energetic, and
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loves changes in technology (Mishra &Jhunjhunwala,
2013). These differences are also attributable to both
generation different personal values that sparks
intrageneration conflicts (Talavera et al., 2018).
Popular beliefs evidently find that the older
generation is risk averse and young members have
tendency to take more risk than those older.
MacCrimmon&Wehrung (1990) self-assessed survey
evidence shows that older executive takes lower risk
as they are not into gambling behavior and have more
understanding regarding many experiences in the
past. This is different from younger member who take
more risk as they have less knowledge so they take
the risk anyway (Grable, 2000). Since prior research
deeply considered that younger age has positive effect
on manufacturing firm efficiency level, our first
hypothesis is as followed:
H
1
: Younger member proportion in Risk Oversight
Committee is positively associated with bank
risk-taking.
2.3 Female
Male and female are commonly perceived as
having different traits. This regular perception has
captivated many researchers to discover more
regarding their differences. Male is associated with
masculinity while female is associated with
femininity. Bem (1977) defines masculinity as quality
of being rational, independent, decisive, and
analytical. On the other side, femininity includes
being expressive, intuitive, sensitive, and warm.
Previous research has identified female positive
relationship towards higher monitoring role that
reduces agency costs. This might be caused by
"offspring risk hypothesis" that explains how woman
may see more risks than man as they see it as a way
to keep safe any offspring under their supervision.
Here, the understanding of more risks might cause the
female to be more protective (Sila, Gonzalez,
&Hagendorff, 2015). The finding is supported by
Harris, Jenkins, & Glaser (2006) research which
found that female is generally less risk averse than
male.
Skała& Weill (2018) found that female board
member, specifically CEO, presence is associated
with lower risk. Here, the Swedish women-leaded
banks are obtaining higher capital to asset ratio and
capital adequacy while the credit risk does not
change. As there is no problem on lower asset quality
here as compared to male-led banks, the attributable
different on capital preferences are linked to higher
female risk aversion. The finding on how higher
female proportion leads to lower risk-taking is
supported by various literature (Bucciol&Miniaci,
2011; Dong, Meng, Firth, &Hou, 2014; Sun & Liu,
2014). Higher proportion of female board are found
to significantly reduce risk-taking in China (Dong et
al., 2014)and higher proportion of female audit
committee members lead to increasing oversight of
bank management risk. Through various investment
game, Charness&Gneezy (2012) claims to find strong
evidence regarding gender differences in risk-taking.
They found that woman is much more financially risk
averse than men. Therefore, in regards with the risk
oversight committee member proportion, this
research proposes the following hypothesis:
H
2
: Female member proportion in Risk Oversight
Committee is negatively associated with bank
risk-taking
2.4 Experience
Experience is a direct contact or observation
regarding a phenomenon.Lejarraga, Hertwig, &
Gonzalez (2012) find proof that people tend to make
decisions based on experience that makes rare events
having less impact than deserved as compared with
their objective probabilities. A direct experience in
one field causes one understand more about the field
compared to those who does not. This also affects the
familiarity regarding the tasks and knowledge on how
to improve it.
Huckman & Upton (2009) stated that the
cumulative production experience, or learning curve,
plays a central role in organizational and individual
learning. They further found that organization and
individual are developing and innovating routines to
decipher todays problem because of their past
experience.
Eichler & Lahner (2017) and Menkhoff,
Schmeling, & Schmidt (2013) has proven that
previous career experience influence one attitude
when seeing certain phenomenon in the present. This
intangible inclination is proven to be similar for
individuals from similar background. While
Menkhoff et al (2013) further expresses that
experienced manager has lower willingness to take
risk as they are less overconfident to the situation as
compared to the inexperienced ones, Koudijs & Voth
(2016) expresses that general personal experiences
may contributes to risk-taking in various way. This is
also due to whether the experience is positive or
negative (Schneider et al., 2016).
This study aims to find out whether direct bank
risk management experience. The bank risk
management related experience can be defined as
those who have worked in bank-related risk
management division (including the compliance
division, director of the bank, vice president of the
bank, vice director of finance, and risk management
committee). This research offers following
hypothesis:
Do Young, Female, and Experienced Characteristics of Risk Oversight Committee Members Accommodate Bank Risk-Taking? Evidence
from Indonesia
67

H
3
: Bank risk management experienced member
proportion in Risk Oversight Committee is
negatively associated to bank risk-taking
3 METHODOLOGY
3.1 Research Models
The research first model, as described in
Equation 3.1, aims to test the research hypothesis of
whether the young age, female, and risk management
experienced members have a significant effect on
bank risk-taking. The control variables for this
equation are bank size, total asset growth, loan to
deposit ratio, and return on asset. is described in
Equation 3.1.
Equation 3.1. Research Main Model


 

 



 



 



 



 



 



 



 

Here, risk-taking is proxied by gross NPL which
is common to be used in bank risk-taking literature
(Skala, 2018; Berger et al., 2009). Meanwhile, the
research obtained proportion for younger members in
the committee by obtaining median from the whole
sample in order to get objective relative younger and
older age of risk oversight committee members,
researcher first collect data of all age for the whole
sample. Once obtained, the research puts '1' for
members with the age equal and lower than median
while puts '0' for those who are older. Meanwhile, the
calculation of gender is straightforward using dummy
and then proportionate it to total committee members.
As this research would like to find the impact of direct
bank risk management expertise to risk-taking, this
study accommodates the definition of experts in Aebi
(2012) and Ghafran& O’Sullivan (2017) to the risk
management context. Specifically, this research
defines bank risk management expertise as those who
have worked in bank-related risk management
division (including the compliance division, director
of the bank, vice president of the bank, vice director
of finance, and risk management committee below
the board of director).
3.2 Population and Sample
Sample selection is done using non-probability
and purposive sampling method. The information
regarding these banks are hand-collectedly obtained
from every bank annual report. The classifications are
general bank listed in the Indonesian Stock Exchange
during the year 2012 - 2016, bank which published
complete annual report, bank that does not undergo
corporate action (eg. merger) during the period of
study, bank that does not undergo extreme trouble
(eg. liquidity shot from government), and bank with
complete data as needed by the research.
4 RESULT AND DISCUSSION
4.1 Descriptive Statistics Analysis
The total observation in the study is 135
observations as the samples are twenty-seven banks
during the period of five years. The panel variable is
bank names and the time variable is year with delta of
one year. Furthermore, the pool of data is strongly
balanced, meaning that there is no empty data point
in the dataset used on this research. The table
detailing descriptive statistics could be seen on
Appendix A.
As for YOUNG, this research approaches the
characteristics by first finding the median age in the
whole risk oversight committee member to know the
comparatively relative older and younger individuals.
The study found that the median of the whole sample
which is 59 years old. This means that those above 59
is considered as 'older' and those below or equal to 59
is considered as 'younger'. The proportion of younger
members compared to the whole committee in each
bank-year is then computed manually. Moreover, the
minimum proportion is zero and the maximum
proportion is one meaning that there are banks which
prefer complete older or younger committee
members. Overall, there are eight bank-year with zero
younger members proportions and ten bank-year
which have all of its members being young.
Here, the mean proportion of FEMALE member
in risk oversight committee is 13.46% with the
median of zero as most banks does not have risk
oversight committee. Female is non-existent in
eighty-one bank-year risk oversight committee.
Risk management experience (EXPER) aims to
explain the proportion of risk oversight committee
members who have directly worked in banking risk
management divisions. The data has shown that the
average proportion of risk oversight committee
members which has directly managed banking risk
management is 22.82%. The minimum proportion of
this trait is zero which consists of eleven banks.
Conversely, the maximum proportion is one in 62
banks which means that some bank-year picks
members with previous experience of direct risk
management exposure in the field.
4.2 Statistical Tests
Testing panel data regression models through
Chow Test, Breusch Pagan, Langrange Multiplier and
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68

Haussman test concludes that the best regression
model for this research is the random effect model.
Meanwhile, the classic assumption tests results show
that the research model is free from the problem of
normality, autocorrelation and heteroscedasticity.
Centering for variable LDR and BANK SIZE treats
the multicollinearity problem. The results of the
random effect regression testing in this research are
described in Appendix B. Additionally, the research
also includes sensitivity testing towards bank risk-
taking using committee average age as alternative
proxy of young, loosening definition of experience by
including of overseeing committee experience, and
existence of woman in the committee which is not
attached in the paper due to page limitation.
4.3 Main Model Analysis
4.3.1 Impact of Increasing Young Age
Proportion to Risk-Taking
As for the relationship between the proportion of
younger risk oversight committee members
(YOUNG) and bank risk-taking, Appendix B shows
that the relationship is inverse. The relationship is
negative and significant at α = 5%. This association
rejects the research second hypothesis which is
regarding how increasing younger risk oversight
committee member proportion is expected to increase
bank risk-taking. The relationship could be due to the
fact that the median and mode age of the whole risk
oversight committee is 59 while the mean age is 58.4.
The definition of relatively 'younger' risk oversight
committee could not be directly attributed to the
definition of young by previous researches as the
previous studies considered 'young' at the year much
younger than 59 years old. This is confirmed by Mata
et al. (2011) which conducts literature review on
impact of aging to risky choice. Mata et al. found that
literatures are justifying 'young' at the age range of 18
to 35 years old while considering 'old' at 65 to 85
years old. In other words, the median of 59 years old
clearly shows that the risk oversight committee
members are skewed to the 'old' criteria. The research
has shed light on how Indonesian risk oversight
committee is coming from people from overall the
same generation.
Moreover, the fact that increasing number of
young members are inversely related to risk-taking is
also attributable to the reputational and career
concerns (Serfling, 2014; Holstrom, 1999;
Hirshleifer&Thankor, 1992). The young members
can be replaced more easily and received less
tolerance from the labor market for faultiness
(Hirshleifer&Thankor, 1992). The harsh truth deters
initial inclination towards risk and make the younger
members more inclined to the consensus to avoid
market punishment.
A sensitivity test conducted to know whether
relative age proportion is the right measure by
calculating the mean age of a board which is a
common way to measure 'young' find that using
average age has no significant result to risk-taking. In
other words, the main model (Appendix B) is proven
to be robust.
4.3.2 Impact of Increasing Female
Proportion to Risk-Taking
According to Appendix B regression with panel
data, increasing number of female members in the
risk oversight committee (FEMALE) is found to
increase bank risk-taking asproxied by Non-
Performing Loan over Total Loan. The relationship is
positive and significant at 1% significancy point. The
discovery of this relationship rejects the research
second hypothesis which is how increasing
proportion of female in the risk oversight committee
is expected to decrease bank risk-taking and is
contrary to many various previous literature (Bucciol
& Miniaci, 2011; Dong et al., 2014; Harris et al.,
2006; Skała & Weill, 2018; Sun & Liu, 2014). As this
negative result is significant at α = 1%, it is worth
exploring why the result differs with common
believes. The prominent role of female is also shown
in additional test which shows that the mere existence
of woman supports committee accommodation to
bank risk-taking.
There are various possible reasons on why higher
proportion of female leads to more risk-taking.
Berger et al., (2014) found that increasing number of
women in the board leads to higher portfolio risk.
Berger argues that most of the previous research that
claims women are risk averse investigate woman in
lower-position. Berger argues that the higher-
positioned women are different and they are risk-
takers. The findings are further supported by Adams,
Funk, Barber, Ho, &Odean (2012). They found that
woman is carelessly more risk-loving than man
although they are still having higher benevolence
trait. Woman are, moreover, found to be more risk-
taking as they care less about power perception from
other people compared to the male counterpart.
Women have to understand the context of
decisions they make and comfortable to the
environment in order to pursue higher risk-taking
behavior. When women are familiar to the context of
decision, various evidence shows that they are more
risk-loving (Miller &Ubeda, 2011; Johnson and
Powell, 1994; Levin et al., 1988). The environmental
context fit into this decision as woman have to be in
a condition where there are no excessive stereotypical
perceptions on what woman risk-taking should be.
Do Young, Female, and Experienced Characteristics of Risk Oversight Committee Members Accommodate Bank Risk-Taking? Evidence
from Indonesia
69

This is due to the fact that woman underlying risk-
taking behavior is found to be greatly influenced by
the general view from the society (Ball et al., 2011).
4.3.3 Impact of Increasing Experienced
Proportion to Risk-Taking
This research expects to find the positive or
negative relationship between increasing proportion
of risk-management experienced (EXPER) member
in risk oversight committee to bank risk-taking. As
can be seen on Appendix B, the negative association
strengthens Menkhoff et al. (2013) argument that
existence of direct experience in related field results
on lower risk-taking behavior. This means that the
members are less overconfident towards the
surrounding situations and take more precaution as
they are already familiar regarding the field volatility
(Huckman& Upton, 2009). This condition might
result on higher skepticism on risk management
experienced members that allow them to not be easily
convinced by optimist high-risk action that bank
management may propose.
It is inferred that the insignificant relationship
might be due to the fact that this research handcollect
data for members who have direct banking risk
management experience. Meaning that the ones
counted as having risk management experience got to
obtain experience in the banking industry risk
management division. This means that those
indirectly learn about risk management but never
practice risk management or risk management
practitioners that is not originated from banking
industry does not count as risk management
experienced members in this research. In other words,
this may mean that board of commissioner select
other factors, such age and gender, as more important
thing of consideration than direct bank risk
management experience as risk management
expertise could also be obtained in other industries or
through certification. The finding suggests that even
though the existence of member with risk
management expertise in the bank risk oversight
committee is compulsory, banking sector specific risk
management experience is not significant in affecting
risk-taking. The finding is further strengthened by
sensitivity test 2 (Table 4.4.) which loosen the
definition of bank risk management to include
previous risk oversight committee experience also
found the same result.
4.3.4 Other Factors Impacting the
Relationship between Risk Oversight
Committee Characteristics and Bank
Risk-Taking
The other factors impacting the relationship
between the committee characteristics and bank risk-
taking are the control variables, consisting of bank
size, total asset growth, loan to deposit ratio, and
return on asset. The relationship between bank size
and bank risk-taking is positive and significant
consistent with Bhagat, Bolton, & Lu (2015). The
larger the bank size, as proxied by total asset, the
more leverage it could bear and the more trustworthy
it gets from the stakeholders. As the bank would like
to keep their position as one of the largest in the
industry, these banks may take to be able to earn
more.
Total asset growth shows the result of bank
strategy year by year. Here, asset growth has an
inverse relationship with bank risk-taking and this is
significant at α = 1%. The condition infers that lower
asset growth results in higher risk-taking. When bank
strategy results in lower asset growth, bank would
then prefer to take more risk to try to obtain more
growth.
The correlation between loan to deposit ratio is
not significant. This is contrary to Skala (2018) which
found that the correlation of LDR to risk-taking is
positive and significant. This means that the risk-
taking decisions bank conducts and overseen by the
risk oversight committee does not look at the amount
of loan to deposit ratio and rather look at other factors.
Return on asset relationship to bank risk-taking is
negative and significant at α = 5%. This result is
consistent with Srairi (2013) and Affan (2014)
finding on return on asset also display a strong
negative association to credit risk. This shows that
banks with lower profitability is aiming to take more
risk to save and improve its position.
5 CONCLUSIONS
5.1 Conclusions
This research is aimed to understand the
unexplored realm of risk oversight committee
characteristics and its tendency to tolerate bank
management risk-taking behavior. The characteristics
that are specifically explored here are young, female,
and risk-management experience. This research uses
random effect panel data estimator and use novel
dataset on 27 banks from 2012 - 2016. The model has
a F-test significance at 1% implying that the model is
highly reliable in explaining bank risk-taking.
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This study has found that increasing proportion of
young risk oversight committee members decreases
committee accommodation towards bank risk-taking.
This is due to the fact that risk oversight committee
members are relatively old and not suitable to risk-
taking literature's definition of young. The median
age of the risk oversight committee member is 59 and
the average age is 58.3 which could be defined as old
age. Although the findings are contrary to the
hypothesis, previous study suggests that the
difference might also be dued to the reputation and
bargaining power of members inside the committee.
Younger manager is proven to deter on making
mistakes as they face less career safety as they have
less reputation and face higher pressure from the
labor market. Sensitivity test conducted shows that
average age which is believed as measurement of
young committee, as opposed to proportion of young
age members, is not significant to impact bank risk-
taking.
On the other hand, increasing proportion of
female risk oversight committee members increases
the committee accommodation towards bank risk-
taking behavior. The result is contrary to the
hypothesis as well as the popular belief that women
are risk-averse and that they are less inclined to make
change. Woman in the higher position, like risk
oversight committee members, are expected to take
different decision than most woman and these
decisions are very likely to be accommodating risky
behavior. Moreover, it is understood that in woman's
nature that if a woman is familiar with the context of
a decision and the environment support woman to do,
woman is more inclined to take on risks. Sensitivity
test conducted shows that the existence of at least one
woman in the risk oversight committee impacts bank
risk-taking behavior accommodation positively. This
means that female existence in the committee plays a
strong role in Indonesia's bank risk-taking tolerance.
Moreover, risk management experienced risk
oversight committee members have negative impact
to bank risk-taking behavior. However, the
relationship is not significant. The result is negative
as more experienced members have more work
experience which make them more aware of risk
consequence. Moreover, they are also more scseptical
and less overconfident when presented by bank
management opportunistic plan. Reasoning for
insignificant result could be from the data limitation
which depends on each bank annual report that might
not report the risk management experience.
Furthermore, the result could also be influenced by
the fact that board of commissioner select other
factors, such age and gender, as more important thing
of consideration than direct bank risk management
experience as risk management expertise could also
be obtained in other industries or through
certification. Sensitivity test conducted when loosen
the risk management experience criteria to include
members who have been risk oversight committee in
the previous years have shown the result of not
significant. The finding enhances understanding that
characteristics other than experience are considered
more important to impact bank risk-taking in
Indonesia.
5.2 Suggestions for Future Research
The research is limited to the usage of sample on
national conventional banks from 2012 to 2016. The
data obtained, moreover, are solely due to each bank
annual report. There might have been information,
such as risk management experience that the
members experience but not written in the annual
report, that might have not been captured in this
research. The research also limits its risk-taking
proxy to the non-performing loan ratio which
specifically measures bank credit risk. Lastly,
demographic data regarding gender is limited to
whether the person is male or female
Based on the limitations of the study, we can
conclude some suggestions for further research
including increasing the scope of the research,
conduct more exploratory research in the field of risk
oversight committee, employ other risk-taking, and
conduct more rigorous research on demographic data
such as specific educational backgrounds or previous
experiences.
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APPENDIX
Appendix A: Descriptive Statistics
Variable
Mean
Std. Dev.
Min
Max
Median
RISK-TAKING
0.0245
0.0156
0.0014
0.0824
0.0233
YOUNG
0.5164
0.2463
0.0000
1.0000
0.5000
FEMALE
0.1347
0.1747
0.0000
0.6667
0.0000
EXPER
0.2282
0.2706
0.0000
1.0000
0.2000
BANK SIZE (in
billion Rupiah)
158,233
0.2300
2,541
1,038.706
69,703
ASSETGROWTH
0.1538
0.1355
-0.2926
0.675678
0.1470
LDR
0.8485
0.1144
0.5239
1.133
0.8639
ROA
0.0178
0.0181
-0.1115
0.0515
0.0176
Number of observation: 135
RISK-TAKING = Ratio of non-performing loan to total loan, YOUNG = Proportion of younger members in risk
oversight committee, FEMALE = Proportion of female members in risk oversight committee, EXPER = Proportion of
risk management experienced members in risk oversight committee, BANK SIZE = natural logarithm of total asset at
book value, ASSET GROWTH = (

 

)/ 

, LDR = Ratio of total loan to
total deposit, ROA = Ratio of net income to average total asset
Do Young, Female, and Experienced Characteristics of Risk Oversight Committee Members Accommodate Bank Risk-Taking? Evidence
from Indonesia
73

Appendix B: Regression Result of Research Main Model


 

 



 



 



 



 



 



 



 

Variables
Exp. Sign
Coef.
z
P>|z|
CONS
0.0451***
13.61
0.0000
YOUNG
+
-0.0062**
-1.69
0.0438
FEMALE
-
0.0161***
2.86
0.0020
EXPER
-
-0.0008
-0.18
0.4375
ASSET GROWTH
-
-0.0338***
-4.55
0.0000
BANK SIZE
-
0.0026**
2.20
0.0140
ROA
-
-0.7690***
-8.77
0.0000
LDR
-
-0.0001
-0.78
0.1595


within
0.7193
Prob>

0.0000
Number of observation: 135
RISK-TAKING = Ratio of non-performing loan to total loan, YOUNG = Proportion of younger members in risk
oversight committee, FEMALE = Proportion of female members in risk oversight committee, EXPER = Proportion of
risk management experienced members in risk oversight committee, BANK SIZE = natural logarithm of total asset at
book value, ASSET GROWTH = (

 

)/ 

, LDR = Ratio of total loan to
total deposit, ROA = Ratio of net income to average total asset
*** significant at  = 1%; ** significant at  = 5%; * significant at  = 10%
SEABC 2018 - 4th Sriwijaya Economics, Accounting, and Business Conference
74